Search results for: Atomic data

Authors: C. L. Popa, S. L. Iconaru, A. Costescu, C. S. Ciobanu, M. Motelica Heino, R. Guegan, D. Predoi

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Surface functionalization of ceramic composites with a special focus on tetraethyl orthosilicate (TEOS) and hydroxyapatite (HAp) is discoursed. Mesoporous ceramic HAp-TEOS composites were prepared by the incorporation of hydroxyapatite into tetraethyl orthosilicate by sol-gel method. The resulting samples were analysed by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), Fourier transform infrared (FT-IR) spectroscopy, and Raman spectroscopy and nitrogen physisorption. The removal of Pb2+ ions from aqueous solutions was evaluated using Atomic Absorbtion Spectroscopy (AAS). Removal experiments of Pb2+ ions were carried out in aqueous solutions with controlled Pb2+ at pH ~ 3 and pH ~ 5. After removal experiment of Pb2+ at pH 3 and pH 5, porous hydroxyapatite nanoparticles is transformed into PbHAp_3 and PbHAp_5 via the adsorption of Pb2+ ions followed by the cation exchange reaction. The diffraction patterns show that THAp nanoparticles were successfully coated with teos without any structural changes. On the other, the AAS analysis showed that THAp can be useful in the removal Pb2+ from water contaminated.

Keywords: teos, hydroxyapatite, environment applications, biosystems engineering

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Authors: Sarisa Pinkham, Kanyarat Bussaban

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The research aims to approximate the amount of daily rainfall by using a pixel value data approach. The daily rainfall maps from the Thailand Meteorological Department in period of time from January to December 2013 were the data used in this study. The results showed that this approach can approximate the amount of daily rainfall with RMSE=3.343.

Keywords: daily rainfall, image processing, approximation, pixel value data

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Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri

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In this paper, we considered and applied parametric modeling for some experimental data of dynamical system. In this study, we investigated the different distribution of output measurement from some dynamical systems. Also, with variance processing in experimental data we obtained the region of nonlinearity in experimental data and then identification of output section is applied in different situation and data distribution. Finally, the effect of the spanning the measurement such as variance to identification and limitation of this approach is explained.

Keywords: Gaussian process, nonlinearity distribution, particle filter, system identification

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Authors: Jaya Mathew

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Many organizations are faced with the challenge of how to analyze and build Machine Learning models using their sensitive telemetry data. In this paper, we discuss how users can leverage the power of R without having to move their big data around as well as a cloud based solution for organizations willing to host their data in the cloud. By using ScaleR technology to benefit from parallelization and remote computing or R Services on premise or in the cloud, users can leverage the power of R at scale without having to move their data around.

Keywords: predictive maintenance, machine learning, big data, cloud based, on premise solution, R

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Authors: Sven Gehrke, Johannes Ruhland

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Data is the oil of our time, without them progress would come to a hold [1]. On the other hand, the mistrust of data mining is increasing [2]. The paper at hand shows different aspects of the concept of trust and describes the information asymmetry of the typical stakeholders of a data mining project using the CRISP-DM phase model. Based on the identified influencing factors in relation to trust, problematic aspects of the current approach are verified using various interviews with the stakeholders. The results of the interviews confirm the theoretically identified weak points of the phase model with regard to trust and show potential research areas.

Keywords: trust, data mining, CRISP DM, stakeholder management

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Authors: K. Thiagarajan, K. Saranya, A. Veeraiah, B. Sudha

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This paper presents a novel algorithm for secure, reliable and flexible transmission of big data in two hop wireless networks using cooperative jamming scheme. Two hop wireless networks consist of source, relay and destination nodes. Big data has to transmit from source to relay and from relay to destination by deploying security in physical layer. Cooperative jamming scheme determines transmission of big data in more secure manner by protecting it from eavesdroppers and malicious nodes of unknown location. The novel algorithm that ensures secure and energy balance transmission of big data, includes selection of data transmitting region, segmenting the selected region, determining probability ratio for each node (capture node, non-capture and eavesdropper node) in every segment, evaluating the probability using binary based evaluation. If it is secure transmission resume with the two- hop transmission of big data, otherwise prevent the attackers by cooperative jamming scheme and transmit the data in two-hop transmission.

Keywords: big data, two-hop transmission, physical layer wireless security, cooperative jamming, energy balance

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Authors: Akshata S. Malani, Anagha D. Chaudhari, Rajeshkumar U. Sambhe

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Nanotechnology in pristine sense refers to building of structures at atomic and molecular scale. Meticulously nanotechnology encompasses the nanomaterials with atleast one dimension size ranging from 1 to 100 nanometres.Unlike the literal meaning of its name, nanotechnology is a massive concept beyond imagination. This paper predominantly deals with relevance of nanotechnology in automotive industries. New generation of automotives looks at nanotechnology as an emerging trend of manufacturing revolution. Intricate shapes can be made out of fairly inexpensive raw materials instead of conventional fabrication process. Though the current era have enough technology to face competition, nanotechnology can give futuristic implications to pick up the modern pace. Nanotechnology intends to bridge the gap between automotives with superior technical performance and their cost fluctuation. Preliminarily, it is an area of great scientific interest and a major shaper of many new technologies. Nanotechnology can be an ideal building block for automotive industries, under constant evolution offering a very wide scope of activity. It possesses huge potential and is still in the embryonic form of research and development.

Keywords: nanotechnology, nanomaterials, manufacturing, automotive industry

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Authors: Romeo Botes, Imelda Smit

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In today’s modern age of technology vast amounts of data needs to be processed in real-time to keep users satisfied. This data comes from various sources and in many formats, including electronic and mobile devices such as GPRS modems and GPS devices. They make use of different protocols including TCP, UDP, and HTTP/s for data communication to web servers and eventually to users. The data obtained from these devices may provide valuable information to users, but are mostly in an unreadable format which needs to be processed to provide information and business intelligence. This data is not always current, it is mostly historical data. The data is not subject to implementation of consistency and redundancy measures as most other data usually is. Most important to the users is that the data are to be pre-processed in a readable format when it is entered into the database. To accomplish this, programmers build processing programs and scripts to decode and process the information stored in databases. Programmers make use of various techniques in such programs to accomplish this, but sometimes neglect the effect some of these techniques may have on database performance. One of the techniques generally used,is to pull data from the database server, process it and push it back to the database server in one single step. Since the processing of the data usually takes some time, it keeps the database busy and locked for the period of time that the processing takes place. Because of this, it decreases the overall performance of the database server and therefore the system’s performance. This paper follows on a paper discussing the performance increase that may be achieved by utilizing array lists along with a pull-process-push data processing technique split in three steps. The purpose of this paper is to expand the number of clients when comparing the two techniques to establish the impact it may have on performance of the CPU storage and processing time.

Keywords: performance measures, algorithm techniques, data processing, push data, process data, array list

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Authors: Giulio Rosati, Luciano Sappia, Rossana Madrid, Noemi Rozlòsnik

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The addition of PEG of different molecular weights has important effects on the physical, electrical and electrochemical properties of iron(III)-tosylate doped PEDOT. This particular polymer can be easily spin coated over plastic discs, optimizing thickness and uniformity of the PEDOT-PEG films. The conductivity and morphological analysis of the hybrid PEDOT-PEG polymer by 4-point probe (4PP), 12-point probe (12PP), and conductive AFM (C-AFM) show strong effects of the PEG doping. Moreover, the conductive films kinetics at the nanoscale, in response to different bias voltages, change radically depending on the PEG molecular weight. The hybrid conductive films show also interesting electrochemical properties, making the PEDOT PEG doping appealing for biosensing applications both for EIS-based and amperometric affinity/catalytic biosensors.

Keywords: atomic force microscopy, biosensors, four-point probe, nano-films, PEDOT

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Authors: Nkongho Ayuketang Arreyndip, Ebobenow Joseph

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In this paper, temperature extremes are forecast by employing the block maxima method of the generalized extreme value (GEV) distribution to analyse temperature data from the Cameroon Development Corporation (CDC). By considering two sets of data (raw data and simulated data) and two (stationary and non-stationary) models of the GEV distribution, return levels analysis is carried out and it was found that in the stationary model, the return values are constant over time with the raw data, while in the simulated data the return values show an increasing trend with an upper bound. In the non-stationary model, the return levels of both the raw data and simulated data show an increasing trend with an upper bound. This clearly shows that although temperatures in the tropics show a sign of increase in the future, there is a maximum temperature at which there is no exceedance. The results of this paper are very vital in agricultural and environmental research.

Keywords: forecasting, generalized extreme value (GEV), meteorology, return level

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Authors: Abdulrahman K. Alshegaifi, Chun-Hsi Huang

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Treating data based on its location in memory has received much attention in recent years due to its different properties, which offer important aspects for cache utilization. Stack data and non-stack data may interfere with each other’s locality in the data cache. One of the important aspects of stack data is that it has high spatial and temporal locality. In this work, we simulate non-unified cache design that split data cache into stack and non-stack caches in order to maintain stack data and non-stack data separate in different caches. We observe that the overall hit rate of non-unified cache design is sensitive to the size of non-stack cache. Then, we investigate the appropriate size and associativity for stack cache to achieve high hit ratio especially when over 99% of accesses are directed to stack cache. The result shows that on average more than 99% of stack cache accuracy is achieved by using 2KB of capacity and 1-way associativity. Further, we analyze the improvement in hit rate when adding small, fixed, size of stack cache at level1 to unified cache architecture. The result shows that the overall hit rate of unified cache design with adding 1KB of stack cache is improved by approximately, on average, 3.9% for Rijndael benchmark. The stack cache is simulated by using SimpleScalar toolset.

Keywords: hit rate, locality of program, stack cache, stack data

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Authors: Wajahat Munir, Muhammad Haseeb, Adeel Anjum, Basit Raza, Ahmad Kamran Malik

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Databases are the key components of the software systems. Due to the exponential growth of data, it is the concern that the data should be accurate and available. The data in databases is vulnerable to internal and external threats, especially when it contains sensitive data like medical or military applications. Whenever the data is changed by malicious intent, data analysis result may lead to disastrous decisions. Autonomic self-healing is molded toward computer system after inspiring from the autonomic system of human body. In order to guarantee the accuracy and availability of data, we propose a technique which on a priority basis, tries to avoid any malicious transaction from execution and in case a malicious transaction affects the system, it heals the system in an isolated mode in such a way that the availability of system would not be compromised. Using this autonomic system, the management cost and time of DBAs can be minimized. In the end, we test our model and present the findings.

Keywords: autonomic computing, self-healing, threat avoidance, security

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Authors: Mohammed R. Elkobaisi, Abdelsalam Maatuk

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The search engines are the large scale information retrieval tools from the Web that are currently freely available to all. This paper explains how to convert the raw resulted number of search engines into useful information. This represents a new method for data gathering comparing with traditional methods. When a query is submitted for a multiple numbers of keywords, this take a long time and effort, hence we develop a user interface program to automatic search by taking multi-keywords at the same time and leave this program to collect wanted data automatically. The collected raw data is processed using mathematical and statistical theories to eliminate unwanted data and converting it to usable data.

Keywords: search engines, information extraction, agent system

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Authors: S. C. Sharma, Ankit Gambhir, Rajeev Arya

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In today’s era data security is an important concern and most demanding issues because it is essential for people using online banking, e-shopping, reservations etc. The two major techniques that are used for secure communication are Cryptography and Steganography. Cryptographic algorithms scramble the data so that intruder will not able to retrieve it; however steganography covers that data in some cover file so that presence of communication is hidden. This paper presents the implementation of Ron Rivest, Adi Shamir, and Leonard Adleman (RSA) Algorithm with Image and Audio Steganography and Data Encryption Standard (DES) Algorithm with Image and Audio Steganography. The coding for both the algorithms have been done using MATLAB and its observed that these techniques performed better than individual techniques. The risk of unauthorized access is alleviated up to a certain extent by using these techniques. These techniques could be used in Banks, RAW agencies etc, where highly confidential data is transferred. Finally, the comparisons of such two techniques are also given in tabular forms.

Keywords: audio steganography, data security, DES, image steganography, intruder, RSA, steganography

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Authors: Anushtha Saxena

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This paper examines the process of data monetisation bye-commerce companies operating in India. Data monetisation is collecting, storing, and analysing consumers’ data to use further the data that is generated for profits, revenue, etc. Data monetisation enables e-commerce companies to get better businesses opportunities, innovative products and services, a competitive edge over others to the consumers, and generate millions of revenues. This paper analyses the issues and challenges that are faced due to the process of data monetisation. Some of the issues highlighted in the paper pertain to the right to privacy, protection of data of e-commerce consumers. At the same time, data monetisation cannot be prohibited, but it can be regulated and monitored by stringent laws and regulations. The right to privacy isa fundamental right guaranteed to the citizens of India through Article 21 of The Constitution of India. The Supreme Court of India recognized the Right to Privacy as a fundamental right in the landmark judgment of Justice K.S. Puttaswamy (Retd) and Another v. Union of India . This paper highlights the legal issue of how e-commerce businesses violate individuals’ right to privacy by using the data collected, stored by them for economic gains and monetisation and protection of data. The researcher has mainly focused on e-commerce companies like online shopping websitesto analyse the legal issue of data monetisation. In the Internet of Things and the digital age, people have shifted to online shopping as it is convenient, easy, flexible, comfortable, time-consuming, etc. But at the same time, the e-commerce companies store the data of their consumers and use it by selling to the third party or generating more data from the data stored with them. This violatesindividuals’ right to privacy because the consumers do not know anything while giving their data online. Many times, data is collected without the consent of individuals also. Data can be structured, unstructured, etc., that is used by analytics to monetise. The Indian legislation like The Information Technology Act, 2000, etc., does not effectively protect the e-consumers concerning their data and how it is used by e-commerce businesses to monetise and generate revenues from that data. The paper also examines the draft Data Protection Bill, 2021, pending in the Parliament of India, and how this Bill can make a huge impact on data monetisation. This paper also aims to study the European Union General Data Protection Regulation and how this legislation can be helpful in the Indian scenarioconcerning e-commerce businesses with respect to data monetisation.

Keywords: data monetization, e-commerce companies, regulatory framework, GDPR

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Authors: Xiaoxin Ye, Guoyi Tang

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The effect of electropulsing ultrasonic shock (EUS) on the surface hardening and microstructure of Ti6Al4V alloy was studied. It was found that electropulsing improved the microhardness dramatically both in the influential depth and maximum value, compared with the only ultrasonic-shocked sample. It’s indicated that refined surface layer with nanocrystalline and improved microhardness were obtained on account of surface severe plastic deformation, dynamic recrystallization (DRX) and phase change, which was implemented at relative low temperature and high strain rate/capacity due to the coupling of the thermal and athermal effects of EUS. It’s different from conventional experiments and theory. It’s discussed that the positive contributions of EPT in the thermodynamics and kinetics of microstructure and properties change were attributed to the reduction of nucleation energy barrier and acceleration of atomic diffusion. Therefore, it’s supposed that EUS is an energy-saving and high-efficiency method of surface treatment technique with the help of high-energy electropulses, which is promising in cost reduction of the surface engineering and energy management.

Keywords: titanium alloys, electropulsing, ultrasonic shock, microhardness, nanocrystalline

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Authors: Ali N. Siyal, Saima Q. Memon, Latif Elçi, Aydan Elçi

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Polystyrene (PS) was extracted from Styrofoam (expanded polystyrene foam) waste, so called white pollutant. The PS was functionalized with N, N- Bis(2-aminobenzylidene)benzene-1,2-diamine (ABA) ligand through an azo spacer. The resin was characterized by FT-IR spectroscopy and elemental analysis. The PS-N=N-ABA resin was used for the enrichment and speciation of Cr(III)/Cr(VI) ions and total Cr determination in aqueous samples by Flame Atomic Absorption Spectrometry (FAAS). The separation of Cr(III)/Cr(VI) ions was achieved at pH 2. The recovery of Cr(VI) ions was achieved ≥ 95.0% at optimum parameters: pH 2; resin amount 300 mg; flow rates 2.0 mL min-1 of solution and 2.0 mL min-1 of eluent (2.0 mol L-1 HNO3). Total Cr was determined by oxidation of Cr(III) to Cr(VI) ions using H2O2. The limit of detection (LOD) and quantification (LOQ) of Cr(VI) were found to be 0.40 and 1.20 μg L-1, respectively with preconcentration factor of 250. Total saturation and breakthrough capacitates of the resin for Cr(IV) ions were found to be 0.181 and 0.531 mmol g-1, respectively. The proposed method was successfully applied for the preconcentration/speciation of Cr(III)/Cr(VI) ions and determination of total Cr in industrial effluents.

Keywords: styrofoam waste, polymeric resin, preconcentration, speciation, Cr(III)/Cr(VI) ions, FAAS

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Authors: Yan Cheng, Yijun Shao, James Rudolph, Charlene R. Weir, Beth Sahlmann, Qing Zeng-Treitler

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Supervised predictive models require labeled data for training purposes. Complete and accurate labeled data, i.e., a ‘gold standard’, is not always available, and imperfectly labeled data may need to serve as an alternative. An important question is if the accuracy of the labeled data creates a performance ceiling for the trained model. In this study, we trained several models to recognize the presence of delirium in clinical documents using data with annotations that are not completely accurate (i.e., weakly-supervised learning). In the external evaluation, the support vector machine model with a linear kernel performed best, achieving an area under the curve of 89.3% and accuracy of 88%, surpassing the 80% accuracy of the training sample. We then generated a set of simulated data and carried out a series of experiments which demonstrated that models trained on imperfect data can (but do not always) outperform the accuracy of the training data, e.g., the area under the curve for some models is higher than 80% when trained on the data with an error rate of 40%. Our experiments also showed that the error resistance of linear modeling is associated with larger sample size, error type, and linearity of the data (all p-values < 0.001). In conclusion, this study sheds light on the usefulness of imperfect data in clinical research via weakly-supervised learning.

Keywords: weakly-supervised learning, support vector machine, prediction, delirium, simulation

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Authors: S. M. AL-Shomar, N. B. Ibrahim, Sahrim Hj. Ahmad

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ZnO thin films with various Gd doping concentration (0, 0.01, 0.03 and 0.05 mol/L) have been synthesized by sol–gel method on quartz substrates at annealing temperature of 600 ºC. X-ray analysis reveals that ZnO(Gd) films have hexagonal wurtzite structure. No peaks that correspond to Gd metal clusters or gadolinium acetylacetonate are detected in the patterns. The position of the main peak (101) shifts to higher angles after doping. The surface morphologies studied using a field emission scanning electron microscope (FESEM) showed that the grain size and the films thickness reduced gradually with the increment of Gd concentration. The roughness of ZnO film investigated by an atomic force microscopy (AFM) showed that the films are smooth and high dense grain. The roughness of doped films decreased from 6.05 to 4.84 rms with the increment of dopant concentration.The optical measurements using a UV-Vis-NIR spectroscopy showed that the Gd doped ZnO thin films have high transmittance (above 80%) in the visible range and the optical band gap increase with doping concentration from 3.13 to 3.39 eV. The doped films show low electrical resistivity 2.6 × 10-3Ω.cm.at high doping concentration.

Keywords: Gd doped ZnO, electric, optics, microstructure

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Authors: Dražen Cvitanić, Biljana Maljković

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This paper presents models for predicting operating speeds on tangent sections of two-lane rural roads developed on continuous speed data. The data corresponds to 20 drivers of different ages and driving experiences, driving their own cars along an 18 km long section of a state road. The data were first used for determination of maximum operating speeds on tangents and their comparison with speeds in the middle of tangents i.e. speed data used in most of operating speed studies. Analysis of continuous speed data indicated that the spot speed data are not reliable indicators of relevant speeds. After that, operating speed models for tangent sections were developed. There was no significant difference between models developed using speed data in the middle of tangent sections and models developed using maximum operating speeds on tangent sections. All developed models have higher coefficient of determination then models developed on spot speed data. Thus, it can be concluded that the method of measuring has more significant impact on the quality of operating speed model than the location of measurement.

Keywords: operating speed, continuous speed data, tangent sections, spot speed, consistency

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Authors: Diafat Abdelouahab, Ekhalfi A Hammoudia, Meribai Abdelmalek A, Bahloul Ahmedb

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The present study aimed to characterize 30 honey samples from the Bordj Bou Arreridj region (Algeria) regarding their floral origins, physicochemical parameters, mineral composition and microbial safety. Mean values obtained for physicochemical parameters were: pH 4.11, 17.17% moisture, 0.0061% ash, 370.57μS cm−1 electrical conductivity, 21.98 meq/kg free acidity, and 9.703 mg/kg HMF. The mineral content was determined by atomic absorption spectrometry. The mean values obtained were (mg/kg): Fe, 7.5714; Mg, 37.68; Na, 186,63; Zn, 3,86; Pb, 0,4869 × 10-3 ; Cd, 267 × 10-3. Aerobic mesophiles, fecal coliforms and sulphite-reducing clostridia were the microbial contaminants of interest studied. Microbiologically, the honey quality was considered good and all samples showed to be negative in respect to safety parameters. The results obtained for physicochemical characteristics of Bordj Bou Arreridj honey indicate a good quality level, adequate processing, good maturity and freshness.

Keywords: pollen analysis, physicochemical analysis, mineral content, microbial contaminants

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Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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Authors: Ruixia Liu

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Qinghai-Tibet Plateau has an important influence on the precipitation of its lower reaches. Data from remote sensing has itself advantage and numerical prediction model which assimilates RS data will be better than other. We got the assimilation data of MHS and terrestrial and sounding from GSI, and introduced the result into WRF, then got the result of RH and precipitation forecast. We found that assimilating MHS and terrestrial and sounding made the forecast on precipitation, area and the center of the precipitation more accurate by comparing the result of 1h,6h,12h, and 24h. Analyzing the difference of the initial field, we knew that the data assimilating about Qinghai-Tibet Plateau influence its lower reaches forecast by affecting on initial temperature and RH.

Keywords: Qinghai-Tibet Plateau, precipitation, data assimilation, GSI

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Authors: Mohammed Alrajhi

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Radiological properties of gel dosimeters and phantom materials are often evaluated in terms of effective atomic number, electron density, photon mass attenuation coefficient, photon mass energy absorption coefficient and total stopping power of electrons. To evaluate the water equivalence of such materials for fast neutron attenuation 19 different types of gel dosimeters and phantom materials were considered. Macroscopic removal cross-sections for fast neutrons (ΣR cm-1) have been calculated for a range of ferrous-sulphate and polymeric gel dosimeters using Nxcom Program. The study showed that the value of ΣR/ρ (cm2.g-1) for all polymer gels were in close agreement (1.5- 2.8%) with that of water. As such, the slight differences in ΣR/ρ between water and gels are small and may be considered negligible. Also, the removal cross-section of the studied phantom materials were very close (~ ±1.5%) to that of water except bone (cortical) which had about 38% variation. Finally, the variation of removal cross-section with hydrogen content was studied.

Keywords: cross-section, neutron, photon, coefficient, mathematics

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Authors: Sook Ching Yee, Angela Siew Hoong Lee

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Big data technologies have become a trend to exploit business opportunities and provide valuable business insights through the analysis of big data. However, there are still many organizations that have yet to adopt big data technologies especially small and medium organizations (SME). This study uses the technology acceptance model (TAM) to look into several constructs in the TAM and other additional constructs which are positive affect, negative affect, organizational factor and motivational factor. The conceptual model proposed in the study will be tested on the relationship and influence of positive affect, negative affect, organizational factor and motivational factor towards the intention to use big data technologies to produce an outcome. Empirical research is used in this study by conducting a survey to collect data.

Keywords: big data technologies, motivational factor, negative affect, organizational factor, positive affect, technology acceptance model (TAM)

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Authors: Byung Ho Jung, Ji Eun Shin, Dong Hoon Lim

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Rhipe that integrates R and Hadoop environment made it possible to process and analyze massive amounts of data using a distributed processing environment. In this paper, we implemented multiple regression analysis using Rhipe with various data sizes of actual data. Experimental results for comparing the performance of our Rhipe with stats and biglm packages available on bigmemory, showed that our Rhipe was more fast than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases. We also compared the computing speeds of pseudo-distributed and fully-distributed modes for configuring Hadoop cluster. The results showed that fully-distributed mode was faster than pseudo-distributed mode, and computing speeds of fully-distributed mode were faster as the number of data nodes increases.

Keywords: big data, Hadoop, Parallel regression analysis, R, Rhipe

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Authors: Mona Almansoori, Ahmed Mustafa, Ahmad Elshamy

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Wireless sensor network was formed by a combination of nodes, systematically it transmitting the data to their base stations, this transmission data can be easily compromised if the limited processing power and the data consistency from these nodes are kept in mind; there is always a discussion to address the secure data transfer or transmission in actual time. This will present a mechanism to securely transmit the data over a chain of sensor nodes without compromising the throughput of the network by utilizing available battery resources available in the sensor node. Our methodology takes many different advantages of Z-MAC protocol for its efficiency, and it provides a unique key by sharing the mechanism using neighbor node MAC address. We present a light weighted data integrity layer which is embedded in the Z-MAC protocol to prove that our protocol performs well than Z-MAC when we introduce the different attack scenarios.

Keywords: hybrid MAC protocol, data integrity, lightweight encryption, neighbor based key sharing, sensor node dataprocessing, Z-MAC

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Authors: Madaki Umar Yusuf, Mohd Rizam B. Abubakar

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The survival censored data with incomplete covariate data is a common occurrence in many studies in which the outcome is survival time. With model when the missing covariates are categorical, a useful technique for obtaining parameter estimates is the EM by the method of weights. The survival outcome for the class of generalized linear model is applied and this method requires the estimation of the parameters of the distribution of the covariates. In this paper, we propose some clinical trials with ve covariates, four of which have some missing values which clearly show that they were fully censored data.

Keywords: EM algorithm, incomplete categorical covariates, ignorable missing data, missing at random (MAR), Weibull Distribution

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Authors: Abdeljalil Beniiche

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The limitation with smart contracts is that they cannot access external data that might be required to control the execution of business logic. Oracles can be used to provide external data to smart contracts. An oracle is an interface that delivers data from external data outside the blockchain to a smart contract to consume. Oracle can deliver different types of data depending on the industry and requirements. In this paper, we study and describe the widely used blockchain oracles. Then, we elaborate on his potential role, technical architecture, and design patterns. Finally, we discuss the human oracle and its key role in solving the truth problem by reaching a consensus about a certain inquiry and tasks.

Keywords: blockchain, oracles, oracles design, human oracles

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Authors: Partha Pratim Kalita

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As sound can be converted to light, light can also be deduced to sound. There are technologies to convert light to sound, but there are not many technologies related to the field where sound can be converted to a distinct vibrational sequence of light. Like the laws under which the principles of sound work, there are principles for the light to become quantum in nature. Thus, as we move from sound to the subtler aspects of light, we are moving from 3D to 5D. Either we will be making technologies of 3D in today’s world, or we will be really interested in making technologies of the 5D, depends on our understanding of how quantum 5D works. Right now, the entire world is talking about quantum, which is about the nature and behavior of subatomic particles, which is 5D. In practice, they are using metals and machines based on atomic structures. If we talk of quantum without taking note of the technologies of 5D and beyond, we will only be reinterpreting relative theories in the name of quantum. This paper, therefore, will explore the possibilities of moving towards quantum in its real essence with the Shoonya ecosystem (zero-point energy). In this context, the author shall highlight certain working models developed by him, which are currently in discussion with the Indian government.

Keywords: quantum mechanics, quantum technologies, healthcare, shoonya ecosystem, energy, human consciousness

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